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Gaussian and Non-Gaussian Linear Time Series and Random Fields
Murray Rosenblatt
€ 122.04
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Description for Gaussian and Non-Gaussian Linear Time Series and Random Fields
Paperback. Series: Springer Series in Statistics. Num Pages: 260 pages, biography. BIC Classification: PBT. Category: (P) Professional & Vocational. Dimension: 234 x 156 x 14. Weight in Grams: 409.
Much of this book is concerned with autoregressive and moving av erage linear stationary sequences and random fields. These models are part of the classical literature in time series analysis, particularly in the Gaussian case. There is a large literature on probabilistic and statistical aspects of these models-to a great extent in the Gaussian context. In the Gaussian case best predictors are linear and there is an extensive study of the asymptotics of asymptotically optimal esti mators. Some discussion of these classical results is given to provide a contrast with what may occur in the non-Gaussian case. There the prediction ... Read more
Much of this book is concerned with autoregressive and moving av erage linear stationary sequences and random fields. These models are part of the classical literature in time series analysis, particularly in the Gaussian case. There is a large literature on probabilistic and statistical aspects of these models-to a great extent in the Gaussian context. In the Gaussian case best predictors are linear and there is an extensive study of the asymptotics of asymptotically optimal esti mators. Some discussion of these classical results is given to provide a contrast with what may occur in the non-Gaussian case. There the prediction ... Read more
Product Details
Format
Paperback
Publication date
2012
Publisher
Springer-Verlag New York Inc. United States
Number of pages
260
Condition
New
Series
Springer Series in Statistics
Number of Pages
247
Place of Publication
New York, NY, United States
ISBN
9781461270676
SKU
V9781461270676
Shipping Time
Usually ships in 15 to 20 working days
Ref
99-15
Reviews for Gaussian and Non-Gaussian Linear Time Series and Random Fields
From the reviews: SHORT BOOK REVIEWS "...will make this book useful as a reference source to the more theoretical among time series specialists." ZENTRALBLATT MATH "This publication can be recommended to readers familiar with the basic concepts of time series who are interested in estimation problems in nonminimum phase processes."